Classification of satellite fused data for land use mapping in development plan
Land use mapping in development plan basically provides resources of information and important tool in decision making. In relation to this, fine resolution of recent satellite remotely sensed data have found wide applications in land use/land cover mapping. This study reports on work carried out fo...
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Malaysian Institute of Planners
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iium-132962015-12-23T00:32:43Z http://irep.iium.edu.my/13296/ Classification of satellite fused data for land use mapping in development plan Mohd. Noor, Norzailawati Abdullah, Alias Hashim, Mazlan G Geography (General) GE Environmental Sciences H Social Sciences (General) T Technology (General) Land use mapping in development plan basically provides resources of information and important tool in decision making. In relation to this, fine resolution of recent satellite remotely sensed data have found wide applications in land use/land cover mapping. This study reports on work carried out for classification of fused image for land use mapping in detail scale for Local Plan. The LANDSATTM, SPOT Pan and IKONOS satellite were fused and examined using three data fusion techniques, namely Principal Component Transform (PCT), Wavelet Transform and Multiplicative fusing approach. The best fusion technique for three datasets was determined based on the assessment of class separabilities and visualizations evaluation of the selected subset of the fused datasets, respectively. Malaysian Institute of Planners 2011 Article PeerReviewed application/pdf en http://irep.iium.edu.my/13296/1/MIP_2011_Article_6.pdf Mohd. Noor, Norzailawati and Abdullah, Alias and Hashim, Mazlan (2011) Classification of satellite fused data for land use mapping in development plan. Journal of the Malaysian Institute of Planners, 9. pp. 97-106. ISSN 1675-6215 http://www.mip.org.my |
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institution |
International Islamic University Malaysia |
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Online Access |
language |
English |
topic |
G Geography (General) GE Environmental Sciences H Social Sciences (General) T Technology (General) |
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G Geography (General) GE Environmental Sciences H Social Sciences (General) T Technology (General) Mohd. Noor, Norzailawati Abdullah, Alias Hashim, Mazlan Classification of satellite fused data for land use mapping in development plan |
description |
Land use mapping in development plan basically provides resources of information and important tool in decision making. In relation to this, fine resolution of recent satellite remotely sensed data have found wide applications in land use/land cover mapping. This study reports on work carried out for classification of fused image for land use mapping in detail scale for Local Plan. The LANDSATTM, SPOT Pan and IKONOS satellite were fused and examined using three data fusion techniques, namely Principal Component Transform (PCT), Wavelet Transform and Multiplicative fusing approach. The best fusion technique for three datasets was determined based on the assessment of class separabilities and visualizations evaluation of the selected subset of the fused datasets, respectively. |
format |
Article |
author |
Mohd. Noor, Norzailawati Abdullah, Alias Hashim, Mazlan |
author_facet |
Mohd. Noor, Norzailawati Abdullah, Alias Hashim, Mazlan |
author_sort |
Mohd. Noor, Norzailawati |
title |
Classification of satellite fused data for land use mapping in development plan |
title_short |
Classification of satellite fused data for land use mapping in development plan |
title_full |
Classification of satellite fused data for land use mapping in development plan |
title_fullStr |
Classification of satellite fused data for land use mapping in development plan |
title_full_unstemmed |
Classification of satellite fused data for land use mapping in development plan |
title_sort |
classification of satellite fused data for land use mapping in development plan |
publisher |
Malaysian Institute of Planners |
publishDate |
2011 |
url |
http://irep.iium.edu.my/13296/ http://irep.iium.edu.my/13296/ http://irep.iium.edu.my/13296/1/MIP_2011_Article_6.pdf |
first_indexed |
2023-09-18T20:22:28Z |
last_indexed |
2023-09-18T20:22:28Z |
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1777408198502776832 |